Code red: Big data risk management requires a safety net
When I advise leaders on a strategy that includes data science, I ask them to consider the probability that their great idea won’t bear fruit. It’s a tough space for visionary leaders to enter — their optimism is what makes them great visionaries. That said, most data science ventures don’t turn out, and most leaders aren’t in touch with the reality that the odds are against them. Having a fallback plan makes good sense, and having a fallback plan for your fallback plan makes great sense.
For instance, when I rolled out an upgraded loyalty platform for a large financial transaction processing company in 2010, we built four plans that successively addressed the failed execution of its predecessor plan. Fortunately, we never had to pull the trigger on even the first fallback plan; however, we were fully prepared for any and all scenarios. It’s a prudent approach that I recommend for you as well, because data science is a risky endeavor.
The colors of cautious management
The best leaders have a backup plan for their backup plan. In fact, when running a strategy that incorporates big data analytics, I suggest you have a series of colored plans: green, yellow, red, and blood red (or black).
- Green is your plan of record.
- Yellow is a contingent plan.
- Red doesn’t meet your minimum expectations, but it doesn’t set you strategically backward either.
- Blood red is your worst case scenario.
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